Statistical estimation for fitting wind speed distribution

Wind energy is a prime sector of the composite renewable energy sector which is supposed to be the prime energy producing force in years to come [1]. The ever increasing demand of wind energy and its renewable nature has led to an emphatic push in development of this sector. Wind speed has been one of those important parameters which form the basic element for design of any wind energy system. Thus, in order to build effective systems, exemplary assessment of wind speed deviation is single handedly the most mandatory parameter that is required to be studied. This leads us to investigate probability density functions which are used to describe wind speed frequency distributions. In this paper, we have modeled wind speed characteristics with respect to Weibull, Rayleigh, Gamma distributions and have simultaneously compared them with respect to statistical parameters such as Chi-square error test, Root mean square error and R2 test as ruling criteria to evaluate the pertinence of the respective distribution functions. Weibull and Gamma give a good fit with Weibull giving a better fit.